139 related articles

How to configure Cursor, Codex, Devin, and other AI coding agents for context management, code quality, and cross-tool collaboration. Practical tips on rule files, TDD, and structured context storage.

A deep dive into Waku Agent's four pillars: Loop Engineering, three-tier Memory system, Eval assessment, and the Harness scaffold. Full walkthrough of a local-first AI assistant from task execution to memory consolidation.

AI code spiraling out of control? This article breaks down a three-layer engineering system — Prompt rules, Skill workflows, and Harness feedback loops — with real-world results showing pass rates rising from 70% to 98%.
The Evolution of Coding Agents: A Para…
Coding agents are evolving from reactive code completers to proactive planners. Explore the "think ahead of time" paradigm, Plan-and-Execute architecture, and its impact on developer workflows.

OpenAI's new model reportedly proved the Cycle Double Cover Conjecture in under an hour using 64 parallel sub-agents. The real lesson? In the AI era, knowing how to ask the right questions matters more than knowing how to calculate.

A deep dive into building verifiable, self-evolving Agent automation loops with Claude Code and Codex — covering Loop Contracts, four trigger types, three-phase execution architecture, and Evolve Loops.

A deep dive into AI-powered testing: Cursor Skills, Coze agents, and LangChain multi-agent systems for automated test case generation, BDD, and review workflows.

An in-depth look at agentic coding: how test-driven loops enable AI self-correction, the real limits of LLM benchmarks, and key engineering lessons on context management and human-AI collaboration.

Andrew Ng partners with JetBrains to launch a Spec-Driven Development course, teaching how to direct AI coding agents via spec files to boost intent fidelity and build maintainable production apps.

What is an AI Agent's harness? This article systematically dissects the core components of agent frameworks: context management, tool use, control loops, and caching strategies—revealing why the same model performs so differently across harnesses.

Superpowers is a trending GitHub project that builds an agentic skills framework with Shell scripts, injecting software engineering methodology into AI coding workflows. A deep dive into its architecture and value.

When an intern uses AI to generate professional-looking slop code, stand-ups balloon from 15 to 45 minutes. This article dissects why AI slop is hard to spot and offers practical team solutions.

Alibaba bans Claude Code over security risks, sparking tech community debate. An in-depth analysis of data leakage risks with cloud AI coding tools and the rise of local AI deployment.

Vibe Coding saves time but leaves piles of bugs? This article details the cross-model review workflow: Claude generates, Codex auto-reviews, with Stop Hook and Skill mechanisms building an AI code review system that intercepts problems automatically.

Cursor launches deep Notion integration via the Cursor SDK — @mention Cursor in any Notion doc to trigger a cloud Agent that automatically opens a PR. We break down the workflow, product logic, and real-world limitations.

In the age of AI-assisted programming, how do you make tools like Codex and Claude Code output more stably? This article deeply analyzes SuperPowers and GStack, covering project-level orchestration and module-level code layering to help developers master AI coding.

A deep dive into Harness Engineering — the third phase of AI coding. Based on research across 2,853 GitHub repos, explore agents.md, Skills, MCP, and eight configuration mechanisms to control your AI coding assistant.

Skill and MCP are two core concepts for building AI Agents. Skill encapsulates task execution methodology, while MCP provides a standardized protocol for connecting external tools. This article breaks down their core differences, abstraction levels, and collaboration.

Andrew Ng partners with JetBrains on a new course systematically teaching Spec-Driven Development. By writing high-quality specs, developers can precisely control AI coding agents, eliminate context decay, and boost intent fidelity.

Explore the core features and use cases of the free Mermaid Diagram Editor. Supporting flowcharts, sequence diagrams, Gantt charts and more, it follows the 'diagrams as code' philosophy to enable version-controlled technical documentation for developers and architects.